本論文主要探討小型人形機器人行為模式規劃方法，包含行走、轉彎、側移、踢球、投球、舉重等運動模式，以及機器人自我平衡控制設計。我們透過感知回授的概念將裝置於機器人身上的加速度計與壓力感測器的感知訊號與模糊控制器結合設計一動態平衡控制器，以加強機器人活動的穩定性與適應未知環境的強健性。論文詳細介紹本實驗室所設計的第二代小型人形機器人的整個系統架構，包含機械結構設計與改進之處、核心處理器、影像處理裝置、感測器及電源整合電路與動態平衡控制器的設計方法。最後，透過行走於不平坦路面、舉重、前後走與避障等實驗以驗証本文所提出方法的可行性。

The whole system structure of the second generation of the small size humanoid robot (aiRobot) in our laboratory will be introduced in the thesis in detail. It contains the design and amendment of the mechanical structure, center process unit, image process unit, sensors, and the integrated power circuit board. And all performances will be implemented using the SOPC chip, Altera EP1C12F324C8. The first contribution of this thesis is mainly the planned method of behavior modes of a small sized humanoid robot. The behavior modes include walking, turning, kicking, throwing, and weight lifting. The second contribution is the design of the self-balanced control of the robot. According to the concept of sensory reflex, we combine the signals of the accelerometers and force sensors with a fuzzy controller to design a dynamic balanced controller for the humanoid robot. Through the implementation of the controller, we can strengthen the activity stability and the robustness of adapting to an unknown environment. Finally, the experiment results show that the robot can walk on an uneven floor, execute weight lifting, move forwards and backwards, and reach the goal with obstacle avoidance.

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